Senior Data Scientist, Azure ML Data Backbone

Molex; Fremont (CA); On-site; USD 160,000 - 200,000; Full time

Benefits offered by this job

Comprehensive benefits: medical,Dental

401(k) with company match

Job summary

Molex in Fremont, CA is seeking a Data Scientist to own the data backbone of our Azure-based AI/ML engineering platform. You will turn historical design and simulation results into clean datasets and validate models before they inform design decisions.

You will build ETL pipelines with Azure Data Factory/Databricks, perform DOE and statistical analyses, and develop Power BI dashboards to monitor data and model health. Collaboration with ML engineers and MLOps teams is expected.

Qualifications

• Hands-on experience building and validating AI/ML models.
• 10+ years in a data science role, ideally with engineering, simulation, or scientific data.
• Strong Python and SQL,
• Comfortable with Azure data tools (Azure Data Factory, Azure Databricks, Azure Synapse) or an equivalent cloud data stack.
• Solid statistics grounding: hypothesis testing, regression, DOE, variance/sensitivity analysis.
• Experience with data visualization/dashboarding tools (Power BI or similar).

Responsibilities

• Build and maintain ETL pipelines (Azure Data Factory / Azure Databricks) for ML use.
• Run statistical and exploratory analyses to identify key design parameters.
• Validate model outputs against ground-truth simulations and flag data quality issues.
• Track model and pipeline performance; build Power BI dashboards for visibility.
• Apply DOE principles to sample design space efficiently.

Skills

AI/ML model building

Python (pandas, NumPy, scikit-learn)

SQL

Azure data tools

Statistics (DOE, hypothesis testing)

Power BI or equivalent

Tools

Azure Data Factory

Azure Databricks

Azure Synapse

Power BI

Job description

Molex in Fremont, CA is seeking a Data Scientist to own the data backbone of our Azure-based AI/ML engineering platform. You will turn historical design and simulation results into clean datasets and validate models before they inform design decisions.

You will build ETL pipelines with Azure Data Factory/Databricks, perform DOE and statistical analyses, and develop Power BI dashboards to monitor data and model health. Collaboration with ML engineers and MLOps teams is expected.